
from sentence_transformers import SentenceTransformer
sentences = "This is an example sentence"

model = SentenceTransformer('sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2')
embeddings = model.encode(sentences)
print(embeddings)
print(embeddings.shape)


# import json

# from torch.nn.modules.container import T
# val = json.load(open('D:/coco/captions_train-val2014/annotations/captions_val2014.json', 'r'))


# print (val.keys())
# print( val['info'])
# print (len(val['images']))
# print (len(val['annotations']))
# print (val['images'][0])
# print (val['annotations'][100])

# self.embeddings = [
#     'A bicycle replica with a clock as the front wheel.',
#     'A bicycle replica with a clock as the front wheel.'
# ]
# self.filename = {
#     0 : 202564
# }
# self.embeddings[0]

# s1 T 
# s1 S
# s2 T
# s2 S

# s1 T 
# s2 T 
# s1 S 